Federated edge learning (FEL) is capable of training large-scale machine learning models
without exposing the raw data of edge devices (EDs). Considering that the learning …

Currently, with the widespread of the intelligent Internet of Things (IoT) in beyond 5G,
wireless federated learning (WFL) has attracted a lot of attention to enable knowledge …

Federated learning (FL) is a distributed privacy-preserving paradigm of machine learning
that enables efficient and secure model training through the collaboration of multiple clients …

Methods of synthesis of a special recurrent neural network for the problem of predicting the
coherence band of transionospheric radio channels are investigated. An algorithm for data …

The advancement of technology has turned smart agriculture into a reality. Remote sensors
and detection devices are now widely applied in large-scale agricultural activities, including …

Wirelessly Federated Learning (WFL) holds immense promise for collaborative knowledge-
sharing among distributed edge devices in the Internet of Things (IoT). However, challenges …

On-device Machine Learning (on-deviceML) is the concept of bringing Machine Learning
models to the constraint device itself and making it smarter. Tiny Machine Learning (TinyML) …